• Genomics & Informatics
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• v.10 no.2
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• pp.88-98
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• 2012

Lipoprotein lipase (LPL) plays an essential role in the regulation of high-density lipoprotein cholesterol (HDLC) and triglyceride levels, which have been closely associated with cardiovascular diseases. Genetic studies in European have shown that LPL single-nucleotide polymorphisms (SNPs) are strongly associated with lipid levels. However, studies about the influence of interactions between LPL SNPs and lifestyle factors have not been sufficiently performed. Here, we examine if LPL polymorphisms, as well as their interaction with lifestyle factors, influence lipid concentrations in a Korean population. A two-stage association study was performed using genotype data for SNPs on the LPL gene, including the 3' flanking region from 7,536 (stage 1) and 3,703 (stage 2) individuals. The association study showed that 15 SNPs and 4 haplotypes were strongly associated with HDLC (lowest $p=2.86{\times}10^{-22}$) and triglyceride levels (lowest $p=3.0{\times}10^{-15}$). Interactions between LPL polymorphisms and lifestyle factors (lowest $p=9.6{\times}10^{-4}$) were also observed on lipid concentrations. These findings suggest that there are interaction effects of LPL polymorphisms with lifestyle variables, including energy intake, fat intake, smoking, and alcohol consumption, as well as effects of LPL polymorphisms themselves, on lipid concentrations in a Korean population.

• Journal of the Korean Society of Radiology
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• v.84 no.2
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• pp.427-440
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• 2023

Purpose This study aimed to investigate the correlation between the fat signal fraction (FF) of the fat-dominant bone tissue of the knee joint, measured using the MRI Dixon method (DIXON) technique, and bone mineral density (BMD). Materials and Methods Among the patients who underwent knee DIXON imaging at our institute, we retrospectively analyzed 93 patients who also underwent dual energy X-ray absorptiometry within 1 year. The FFs of the distal femur metaphyseal (Fm) and proximal tibia metaphyseal (Tm) were calculated from the DIXON images, and the correlation between FF and BMD was analyzed. Patients were grouped based on BMD of lumbar spine (L), femoral neck (FN), and common femur (FT) respectively, and the Kruskal-Wallis H test was performed for FF. Results We identified a significant negative correlation between TmFF and FN-BMD in the entire patient group (r = -0.26, p < 0.05). In female patients, TmFF showed a negative correlation with FN-BMD, FT-BMD, and L-BMD (r = -0.38, 0.28 and -0.27, p < 0.05). In male patients, FmFF was negatively correlated with only FN-BMD and FT-BMD (r = -0.58 and -0.42, p < 0.05). There was a significant difference in the TmFF between female patients grouped by BMD (p < 0.05). In male patients, there was a significant difference in FmFF (p < 0.05). Conclusion Overall, we found that FF and BMD around the knee joints showed a negative correlation. This suggests the potential of FF measurement using DIXON for BMD screening.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Korean Journal of Ecology and Environment
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• v.52 no.3
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• pp.210-220
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• 2019

Population growth and the increase of energy consumption due to civilization caused global warming. Temperature on the Earth rose about $0.7^{\circ}C$ for the last 100 years, the rate is accelerated since 2000. Temperature is a factor, which determines physiological action, growth and development, survival, etc. of the plant together with light intensity and precipitation. Therefore, it is expected that global warming would affect broadly geographic distribution of the plant as well as structure and function ecosystem. In order to understand the effect of global warming on the ecosystem, a study about the effect of temperature rise on germination and growth in the plant is required necessarily. This study was carried out to investigate the effects of experimental warming on the germination and growth of two oak species(Quercus mongolica and Q. serrata) in temperature gradient chamber(TGC). This study was conducted in control, medium warming treatment($+1.7^{\circ}C$; Tm), and high warming treatment ($+3.2^{\circ}C$; Th) conditions. The final germination percentage, mean germination time and germination rate of two oak species increased by the warming treatment, and the increase in Q. serrata was higher than that in Q. mongolica. Root collar diameter, seedling height, leaf dry weight, stem dry weight, root dry weight, and total biomass were the highest in Tm treatment. Butthey were not significantly different in the Th treatment. In the Th treatment, Q. serrata had significantly higher H/D ratio, S/R ratio, and low root mass ratio (RMR) compared with control plot. Q. mongolica had lower RMR and higher S/R ratio in the Tm and Th treatments compared with control plot. Therefore, growth of Q. mongolica are expected to be more vulnerable to warming than that of Q. serrata. The main findings of this study, species-specific responses to experimental warming, could be applied to predict ecosystem changes from global warming. From the result of this study, we could deduce that temperature rise would increase germination of Q. serrata and Q. mongolica and consequently contribute to increase establishment rate in the early growth stage of the plants. But we have to consider diverse variables to understand properly the effects that global warming influences germination in natural condition. Treatment of global warming in the medium level increased the growth and the biomass of both Q. serrata and Q. mongolica. But the result of treatment in the high level showed different aspects. In particular, Q. mongolica, which grows in cooler zones of higher elevation on mountains or northward in latitude, responded more sensitively. Synthesized the results mentioned above, continuous global warming would function in stable establishment of both plants unfavorably. Compared the responses of both sample plants on temperature rise, Q. serrata increased germination rate more than Q. mongolica and Q. mongolica responded more sensitively than Q. serrata in biomass allocation with the increase of temperature. It was estimated that these results would due to a difference of microclimate originated from the spatial distribution of both plants.